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MEEM: A Novel Middleware for Energy Efficiency in Mobile Adhoc Network
Author(s) -
Pavan Hiremath,
C. V. Guru Rao
Publication year - 2016
Publication title -
advances in intelligent systems and computing
Language(s) - English
Resource type - Book series
eISSN - 2194-5357
pISSN - 2194-5365
DOI - 10.1007/978-3-319-33622-0_7
Subject(s) - computer science , mobile ad hoc network , computer network , ad hoc on demand distance vector routing , optimized link state routing protocol , distributed computing , energy consumption , middleware (distributed applications) , routing (electronic design automation) , wireless ad hoc network , routing protocol , distance vector routing protocol , selection algorithm , selection (genetic algorithm) , wireless , engineering , telecommunications , network packet , artificial intelligence , electrical engineering
Achieving an enhanced network lifetime is still an open issue in mobile ad hoc network. After years of research and invention, a robust technique to ascertain energy efficiency is yet to be explored especially to overcome an adverse effect of dynamic topology and selection of highly stabilized links during routing. Therefore, we present a very simple and cost-efficient middleware called as MEEM i.e. Middleware for Energy Efficiency in Mobile ad hoc network that offers an effective solution towards this problem. MEEM offers cost effectiveness by enabling the middleware to increase its scope of selection of stabilized routes based on formulating new multiple decision-making parameters e.g. Time for Route Termination, Time for Stable Routing, Frequency of Route Error, Reduction in Signal Attenuation, and Remnant Network Lifetime. The design of MEEM is carried out using quadratic approach thereby retaining parallel processing of an algorithm to enhance the communication performance of the mobile nodes. The outcome of the study was found to excel better results in comparison to frequently used routing protocol e.g. Adhoc On-demand Distance Vector (AODV) and Optimized Link State Routing (OLSR) with respect to energy consumption and algorithm processing time. The algorithm is found to be compliant of time and space complexity thereby results in cost effective solution.

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